Comparison of ionospheric characteristic parameters obtained by GPS and ionosonde with IRI model over China

Abstract

This paper presents a comparison of ionospheric characteristic parameters obtained by a GPS network and three ionosondes at Mohe (122.4 • E, 53.5 • N, dip angle 70.983 • N), Zuolingzhen (114.6 • E, 30.5 • N, dip angle 46.350 • N), and Fuke (109.1 • E, 19.5 • N, dip angle 27.083 • N) located in China with an IRI model in the year 2011. Observed NmF2 and hmF2 values at the three stations are compared with IRI2007 and IRI2012 predictions, respectively. The results show that there are clear linear correlations between the observed values and the IRI model predicted values. The IRI model gives overestimations at the three stations mostly in 2011. For the NmF2 and hmF2 values, most of the results show that the IRI2012 predicted values are closer to the observed values compared with those of IRI2007. Additionally, the GPS TEC values derived from the Crustal Movement Observation Network of China (CMONOC) are compared with the IRI2012 predictions. From the results, it is evident that the IRI2012 model predictions follow the normal trend of diurnal variation of GPS measured TEC monthly means but do not reproduce the measured data well. The IRI2012 model overestimates electron density in the latter part of spring as well as the first half of autumn and winter and underestimates electron density in early spring and the latter part of autumn. Referring to GPS TEC, the precision of the IRI2012 model predicted TEC values is ∼5 TECU over China. It may also be noted that there are two discontinuities of IRI-TEC monthly means appearing in November and December of the year 2011. This brings a bias of ∼3 TECU of TEC values between two adjacent months.

Project Loon based augmentation for global ionospheric modeling over Southern Hemisphere

“…Since IRI is a climatological model, it cannot provide TEC values with the high accuracy as GPS-TEC values. Many authors have reported evaluations of the IRI model over different areas of the world during periods of quiet or active space weather2425262728293031323334353637. The capabilities of and improvements to the IRI model have been shown, but there is not very good agreement between the IRI model predictions and the observed values, especially during periods of active space weather.…”

Prediction of global ionospheric VTEC maps using an adaptive autoregressive model

“…Many scholars have investigated the accuracy of these models for different regions of the world during periods of different solar and geomagnetic activities (Abdu et al 1996;Araujo-Pradere et al 2003;Bertoni et al 2006;Lee and Reinisch 2006;Bhuyan and Borah 2007;Mosert et al 2007;Adewale et al 2011;Nigussie et al 2013;Okoh et al 2013;Olwendo et al 2013;Wichaipanich et al 2013;Wang 2016). The annual mean of the root-mean-square (RMS) of the differences between IGS GIMs and IRI predictions in 2014 was approximately 10 total electron content units (TECU, 10 16 el/m 2 ) .…”